Enterprise computing environments often need to access data relating to a particular business application. In order to avoid a single point of failure, data is often stored at multiple hosts at different locations (e.g., different locations within a given data center, different data centers, and so on). Thus, for example, if a particular data set becomes unavailable from one host (e.g., due to host failure, due to a network partition or other network failure, and so on), a client process may access the data at another host. The individual hosts may not be highly available, but the combination of the individual hosts provides a more highly available solution.
When storing the same data at multiple locations, a problem that is encountered is maintaining consistency between the various copies of the data. The state of the data set as it exists at one host may not be consistent with the state of the data set as it exists at the other host. For example, if a client process has made changes to a data set at one host, and the data set then becomes unavailable from that host, the changes that have been made in the copy of the data set at that host may be lost, at least temporarily. A recent version of the data set may be obtained from another host. However, if the client process starts operating on the data set from the other host, a further problem arises in that two versions of the data set may potentially be created, each with changes that are not reflected in the other data set.
Accordingly, an on-going need exists for systems and methods that are capable of providing highly available data. It should be appreciated that, although certain features and advantages are discussed, the teachings herein may also be applied to achieve systems and methods that do not necessarily achieve any of these features and advantages.